The pharmaceutical sector is more and more going in the direction of using living systems to produce the drugs, also known as biopharmaceuticals. The innovative capacity for biopharma firm has proven to be high, making them interesting sources for new innovative drugs for the market. Bringing a new medical drug to the market is a long and challenging process for companies. The average cost is about $1 billion with a time frame of 10 to 15 years from that an innovative idea is created until a drug is successfully launched in the market, and far from all ideas makes it all the way. This phase is also known as the ‘Valley of Death’, which only by the name indicates how difficult a trip across here is. However, many biopharma firms are still small in size compared with the huge pharma firms, and therefore have quite some troubles when traveling through the valley of death. In other words, they commonly lack key resources and capabilities to make it to the market. The purpose of the thesis report is to explore the valley of death in the biopharmaceutical sector. The focus is to understand how biopharma firms experience the phase, and to identify key actors and factor that play a role here, and their interconnections to each other. Moreover, the aim is to identify various strategies that biopharma firms can use to overcome the barriers that stand in the way of successfully introducing an innovative product in the market. The main research question used was ‘What are key actors, factors and strategies that impact how biopharma companies move a radically new product from invention to a first market introduction?’ In order to investigate this topic further, exploratory research was done to contribute to the current lack of understanding the valley of death in a comprehensive way. The research approach consisted of a combination of three different methods, to cover both theoretical and practical aspects on the topic. Additionally, the three methods were combined to tackle the exploratory research, since it wasn’t known in advance where the most information would be found. The first method was systematic literature review, which studied the current literature stream from the search phrase ‘valley of death’ in the title of the articles. The second method was carrying out interviews within the organization of Vintura, a consultancy firm focusing on life sciences and health care topics. Finally, the third method was company interviews with four biopharma firms, by interviewing two persons within each firm. Each method was used to answer all the sub questions in the thesis, and in the end all the results were consolidated into final answers to the sub questions, leading up to an answer for the main research question. The literature review provided information from a historical and academic perspective, however the literature on the valley of death is quite limited. The Vintura interviews provided a practical approach for the topic, with more interconnections and strategies described. Finally, the company interviews with the biopharma firms gave insights straight from the firms themselves, on how they experience the innovation process and its challenges. The interview set-up for the biopharma company interviews was interactive, resulting in interesting visual overviews of interconnections between actors and factors. The combination of all results provided good answers to the sub questions, and in total to the main research question. The valley of death is an uncertain and risky phase for companies that takes between 10 to 15 years to complete. Overall, the results show that biopharma firms should aim to achieve six goals in the valley of death: (1) develop the right product, (2) find sufficient funding, (3) have the right skills & resources at the right time, (4) make an intellectual property set-up, (5) plan & execute clinical trials, and (6) increase product development speed. In other words, aiming to reach these goals in the best way would provide a higher chance to deal with the valley of death successfully. Moreover, many key actors and factors were found. Examples of actors are regulatory authorities, contract organizations, hospitals, and various scientists, while some examples of factors are design of clinical trials, access to capital, and human resources. The thesis results also provided many relations and interconnections between actors and factors, connected to the six main goals presented. As an example, in order to work towards the goal to develop the right product, the actor ‘project manager’ in combination with the factor ‘leadership skills’ showed to be a critical element needed to get a good process running. Similar interconnections were found for other actors and factor per main goal. Finally, many strategy suggestions were identified from all the research methods, with specific links between a strategy and a barrier. An example of a strategy is ‘evaluate knowledge gained in clinical trials and tackle issues’, when dealing with commercial issues with the product. From all the results in the thesis, a theoretical model was created to visualize causal relationships between actors, factors and strategies in the valley of death. The model shows an overview of the six goals, with a detailed sub model per goal explaining the dynamics and connections. The model consists of the following elements: (1) a goal, which is one of the six main goals, (2) facilitators, which are actors or factors that positively contribute to reach the goal, (3) barriers, which are actors or factors that are blocking the goal, and (4) strategies, which are specific suggestions on how to tackle each barrier. Overall, this model provides a visual and practically usable tool to understand the main mechanisms in the valley of death, and concrete suggestions on how to increase the chances to survive the valley of death. The model can have a managerial impact for biopharma firms, by offering an overview of the key goals and the challenges. Furthermore, the model adds to the literature and previous research by providing an overview of interconnections and strategies that previously could not be found in the literature. It is recommended to verify the model through further research, by qualitative or quantitative approaches to find out if companies in the biopharma sector agree with it. Moreover, the model could partly be valid for the pharmaceutical industry, or be adapted to other relevant high-tech industries, which can then be investigated in future research.